In industrial production, workers need to wear safety helmets at all times. However, due to different lighting, viewing angles, and the tendency of people to block each other, the precision of target detection is not high enough. Aiming at this problem, a real-time detection of helmets was achieved by improving the YOLOv5 algorithm. This algorithm introduces the lightweight network structure FasterNet, which uses partial convolution as the main operator to reduce the amount of calculations and parameters of the network; the boundary regression loss function Wise-IoU loss function with a dynamic focusing mechanism replaces the original loss function in YOLOv5; finally, the CBAM attention mechanism is introduced to obtain global context information and improve the detection ability of small targets. The experimental results show that the parameters of the improved YOLOv5 model are reduced by 12.68%, the computational amount is reduced by 10.8%, the mAP is increased from 88.3 to 92.3%, and the inference time is reduced by 81.5%, which is better than the performance of the original model and can detect helmet wearing effectively and in real time.

To enhance the friction and wear properties of 40Cr steel’s surface, CoCrFeMnNi high-entropy alloy (HEA) coatings with various Ti contents were prepared using laser cladding. X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS) were used to characterize the phase composition, microstructure, and chemical composition of the samples. The findings demonstrated that the CoCrFeMnNiTi_x HEA coatings formed a single FCC phase. Fe₂Ti, Ni₃Ti, and Co₂Ti intermetallic compounds were discovered in the coatings when the molar ratio of Ti content was greater than 0.5. The EDS findings indicated that Cr and Co/Ni/Ti were primarily enriched in the dendrite and interdendrite, respectively. Ti addition can effectively enhance the coating’s mechanical properties. The hardness test findings showed that when the molar ratio of Ti was 0.75, the coating’s microhardness was 511 HV0.5, which was 1.9 times the hardness of the 40Cr (256 HV0.5) substrate and 1.46 times the hardness of the CrCrFeMnNi HEA coating (348 HV0.5). The friction and wear findings demonstrated that the addition of Ti can substantially reduce the coating’s friction coefficient and wear rate. The coating’s wear resistance was the best when the molar ratio of Ti was 0.75, the friction coefficient was 0.296, and the wear amount was 0.001 g. SEM and 3D morphology test results demonstrated that the coating’s wear mechanism changed from adhesive wear and abrasive wear to fatigue wear and abrasive wear with the increase in Ti content.

Due to its unique single-phase multivariate alloy characteristics and good low-temperature mechanical properties, CoCrFeNiMn high entropy alloy (HEA) has attracted the interest of many researchers in recent years. In this paper, to improve the wear resistance of Q235 alloy steel surface, CoCrFeNiMnSn_x HEA coatings were prepared on the surface of Q235 steel via laser cladding. X-ray diffractometry, optical microscopy, scanning electron microscopy (SEM), and energy dispersive spectrometry were used to determine the microstructure and chemical composition. The research findings revealed that the CoCrFeNiMn HEA coatings were formed from a single FCC phase. As the Sn content in the coating increased, a new MnNi₂Sn phase formed. Microhardness and friction and wear results showed that when the mole content of Sn was 0.2, the hardness of the CoCrFeNiMn HEA coating was increased by approximately 45%, the friction coefficient decreased by 0.168, and the wear loss decreased by 16.6%. Three-dimensional noncontact morphology and SEM results revealed that the wear mechanisms of CoCrFeNiMn HEA coatings were abrasive wear, delamination wear and a small amount of oxidative wear under dry friction conditions, whereas the friction mechanisms of CoCrFeNiMnSn_0.2 HEA coatings were primarily abrasive wear and oxidative wear.

A measurement method based on the homography matrix and partial area effect is studied to improve the precision of the visual measurement of the bearing size. Firstly, the camera is calibrated to obtain its distortion coefficient, and the image is corrected for distortion. Secondly, the relationship between the pixel plane and the bearing imaging plane is determined by solving the homography matrix with a chessboard. Finally, the sub-pixel edge contour of the bearing is obtained through the improved partial area effect, and the pixel coordinates are mapped to the world coordinates according to the homography matrix. The feature size is obtained by fitting the mapping points. Experimental results showed that the transformation of the homography matrix is more accurate than the pixel equivalent in the process of converting the pixel size to the actual size. The improved partial area effect sub-pixel edge detection results are better than the partial area effect and Zernike moment. The measurement error for the bearing outer diameter is less than 0.05 mm and is within 0.5 pixel.

In order to solve the problem of constant force control in the robot grinding process of a centrifugal pump housing a circular inner surface, this study used the force–position hybrid control mode based on a pneumatic servo system to realize the constant control of grinding force. In this process, the manipulator realizes the position and pose control of the end grinding device, and the end grinding device realizes the constant force control in the grinding process. The mathematical model of the pneumatic system is established and linearized by using the gas balance state equation, the adiabatic equation of the isentropic process, and the Sanville flow equation. The balance equation of the cylinder piston was established by using Newton’s second law, the transfer function of the contact force between the grinding device and workpiece was obtained, and the stability of the pneumatic control system was determined by the Hurwitz criterion. The PID algorithm was used to improve the displacement response speed of the system and eliminate the impact and oscillation in the force response. The feasibility, stability, and robustness of the system were verified by simulation experiments. This method has the advantages of simple control, a small amount of calculation, and a fast response, as well as providing a feasible scheme for the popularization and application of robot grinding technology.

To improve the calibration accuracy of a vision measurement system, a checkerboard corner detection method based on linear fitting of the checkerboard local contour is proposed. First, by binarization and morphological dilation of the checkerboard image, the coordinates of two adjacent vertices of adjacent dark squares are obtained; the midpoint of the two vertices is taken as the reference point; the reference dotted array is obtained; and the Zernike moment subpixel method is used to obtain the checkerboard contour data points in the neighborhood of each reference point. Finally, the contour points are classified according to the orientation based on the reference points; two intersecting lines are fitted; and the intersection of the two lines is exactly the corner point that we want to find. A camera calibration experiment was conducted on the same group of checkerboard images. The results show that the calibration results of the corner points obtained based on this method are highly consistent with the OpenCV library function method and the MATLAB Toolbox calibration method, and the reprojection error is smaller. At the same time, it is robust to changes in the light source brightness.